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Sobre esta vaga de Computer Vision Engineer na Observable Space

Observable Space · Híbrido · Los Angeles, CA

We are seeking a highly experienced and motivated Computer Vision Engineer to join our dynamic team. Join a rockstar team of experienced entrepreneurs, engineers, scientists and astronomers from SpaceX, DARPA, SmartThings, and Bird. This role will report to the CTO.

Responsibilities

  • Stay abreast of the latest advancements in SDA/SSA, Photometry, and novel image processing techniques by regularly reviewing research papers and publications.

  • Collaborate with software development teams to conceptualize, develop, and implement proof of concept based on cutting-edge research.

  • Evaluate, train, and customize combination models based on state of the art backbones (Unet, vision transformer, resenet, etc)

  • Own our image processing pipelines from end to end - from camera sensor readout to publishing extractions to our cloud data warehouse.

  • Design and generate simulated data for rapid testing of proof of concept algorithms.

  • Coordinate with operations and engineering teams to gather real-world data for validating algorithms against synthetic test cases.

  • Lead complex multidisciplinary research projects, ensuring detailed and rigorous scientific processes.

  • Effectively communicate complex research findings to both technical and non-technical stakeholders, providing clear and concise insights.


Basic Qualifications

  • 10+ years of experience in a relevant commercial or academic research field.

  • Strong foundation in mathematics or computational mathematics.

  • Strong and demonstrated programming ability in C++ or C in a professional environment

  • Demonstrated experience in first principles engineering and science.

  • Detail-oriented with the ability to manage and execute complex, multidisciplinary research projects.

  • Experience in machine learning model training using PyTorch or TensorFlow.

  • Experience in classical vision techniques with an emphasis on OpenCV.


Preferred Qualifications

  • Masters or Ph.D. in Engineering, Mathematics, or a related field of study.

  • Experience in machine learning model training using PyTorch or TensorFlow.

  • Knowledge or experience in astrodynamics.

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